System and method for synchronizing wireless devices without sending timestamp data

ABSTRACT

A sensor network includes a plurality of sensors and a base station for sending a series of data acquisition requests to the sensors. Each data acquisition request has an index. Each sensor has a synchronization calculation module and an internal clock. The sensors are adapted and configured to receive the series of data acquisition requests and record a timestamp of receipt for each data acquisition request. The sensors also store a predefined time interval related to the plurality of data acquisition requests so that the sensor can calculate a time to start collecting data based upon the series of data acquisition requests, the timestamps, the indices, and the predefined time interval. In an alternative embodiment, the base station only sends a general request for data acquisition and a synchronization sensor module receives the general request and, in turn, sends the series of data acquisition requests to the sensors.

BACKGROUND OF THE DISCLOSURE

1. Field of the Disclosure

The subject disclosure relates to communication in sensing, monitoringand control systems, and more particularly to synchronizing wirelessdevices used on board aircraft without sending timestamp data.

2. Background of the Related Art

In recent years, the aerospace industry has been actively working onusing wireless communication as a replacement or augmentation for wireddata connections in aircraft systems. Some benefits of wireless asopposed to traditional wired sensors include weight and complexityreductions, simplified installation and maintenance, easier systemreconfiguration as well as better diagnostic capabilities. Additionally,new sensing technologies and aircraft subsystems are enabled byutilizing wireless technology, which eliminates additional design andinstallation costs and limits the additional wiring weight.

Mechanical and structural health monitoring and diagnostic systemsparticularly benefit from wireless technology. At present, wider use ofsuch systems is hampered by the increased cost and complexity of therequired wiring, which can often outweigh the potential gains. If noadditional wiring were necessary, such systems might be more readilyused, which would lead to significant improvements in maintenance costsand in aircraft reliability.

Most sensing and control systems require some degree of synchronicitybetween different elements. For example, a mechanical diagnostic systemmay acquire vibration data from multiple sensors. For correctinterpretation of multi-dimensional vibration data, it is necessary tomake sure that the acquired signals correspond to the same intervals intime. The synchronization is typically achieved in one of two ways. Thefirst approach is to devise a method to make sure that all sensors starttheir data acquisition at the same time. The second approach is to haveall sensor nodes measure their local time according to well synchronizedclocks.

The two approaches to synchronization are in fact equivalent. If it ispossible to command several sensor nodes to perform a certain taskstarting at the same time, then the task may involve starting orresetting their clocks. If clock resets are done simultaneously, thenthe clocks will be closely synchronized for some time provided theirrates do not differ too much. On the other hand, if the clocks aretightly synchronized, then the sensors may be commanded to perform thetask of interest, such as to start data acquisition, at particular timevalues according to their clocks. In other words, the respectivesensor's reading can be correlated in such a way that the readingscorrespond to the same physical time instance.

Several techniques for synchronization of wireless devices are known andtypically involve exchanges of time-stamped messages. Based on knownsend and receive times of sent messages, offsets and rate differencesmay be estimated between the clocks of those devices. For example, see“Protocols and architectures for wireless sensor networks” by HolgerKarl and Andreas Willig, (published by John Wiley & Sons, Ltd. in theyear 2005, which is incorporated herein by reference. See also U.S.patent application Ser. No. 12/941,226, filed on Nov. 8, 2010 andentitled APPARATUS AND METHOD FOR SYNCHRONIZING WIRELESS DEVICES andU.S. patent application Ser. No. 12/799,087, filed on Apr. 16, 2010 andentitled SYNCHRONIZING WIRELESS DEVICES, each of which is incorporatedby reference herein in its entirety.

Some common approaches rest on the assumption that propagation andprocessing delays of the messages are symmetric and statisticallyconstant in time. That is, it is assumed that any random delays indelivering a message from wireless node N1 to the wireless node N2 aredistributed in the same way as message delivery delays from wirelessnode N2 to wireless node N1, and this statistical distribution isstationary in time. Furthermore, the accuracy of the resulting clocksynchronization depends on the variability of message delivery delays.Generally, as the variance of message delivery delays gets larger, sodoes the synchronization error. Therefore, for synchronization to beaccurate in this approach, it is desirable to have as little variance inmessage delivery delays as possible.

SUMMARY OF THE INVENTION

There are problems associated with high level communication protocolswhen synchronizing is required because there is uncertainty about theexact time of delivery. The latency of a particular message cannot befully predicted due to high level protocols such as TCP using multiplesoftware layers as well as complicated acknowledgement, retransmission,and packet scheduling algorithms. The unpredictable latency creates adifficulty with performing synchronization of end devices using thesehigh level protocols. Further, the timestamp methods lead to longerradio operation and consequently higher energy use.

The subject disclosure provides wireless technology that meets orexceeds the same requirements for performance and reliability aspreviously used wired systems. One possible advantage is to eliminatetwo-way data exchange. Another possible advantage is to shorten theoverall duration of synchronization as well as the transmission time.Some radio technologies use more energy when transmitting and less whenlistening/receiving, but for some radios there is little difference.Thus, another potential advantage to save energy is to put the radiomodule into a low-power sleep mode more frequently or for a longerperiod of time.

The subject technology addresses energy usage in wireless sensornetworks. If a sensor is powered by a battery or like storage device,the battery must last for years before replacement. Particularly foraircraft applications, the battery should last from major scheduledmaintenance to major scheduled maintenance. Unscheduled maintenance forbattery replacement would be downtime that results in increasedmaintenance cost and flight delays. Low power consumption also helps toreduce battery size and lighten the overall system.

An alternative to battery operation is to power the wireless sensorsfrom energy harvesting or scavenging devices. Such devices typicallyhave low power output levels unless the size and weight are increased.Again, minimizing the power consumption advantageously improves systemqualities.

The subject disclosure also has recognized and addressed the need toeffectively synchronize wireless sensors that operate as subordinatenodes in a star network configuration. The subject disclosure eliminatesthe need to explicitly include timestamp data in messages between thesensors and the base station. As can be seen in view of the above, themessage exchange protocol is simplified, the synchronization process isfaster, and energy usage is reduced leading to longer battery life.

Typically, the radio module consumes the largest amount of energy, usinga large portion to transmit messages. Significant amounts of energy arealso used when the radio module is listening for or receiving messages.As such, reduction of the number and length of transmissions as well asthe length of the listening and receiving period will greatly saveenergy. The subject technology reduces the length of time it takes whenthe sensor's radio module must be active to perform synchronization, andeliminates the need to send data transmissions from the sensors to thebase station during the synchronization period. Whenever receiving ortransmitting radio messages is not necessary, the radio module can beput in a sleep state. Shortening and simplifying the synchronizationprocess leads to significant energy savings on the sensor.

Further, the subject technology recognizes the advantages of distributedsynchronization rather than centralized synchronization. Typically, dataconcentrator units acquire data from multiple sensor units, whereindifferent types of sensors all can communicate with the same dataconcentrator unit. However, each sensor may have differentsynchronization requirements. For example, acceleration sensors requiretighter synchronization than temperature sensors. In view of the above,it is desirable to move the synchronization tasks to the sensors, if notcompletely, then as much as possible.

In one embodiment, the subject technology is directed to a method forsynchronizing a plurality of sensors without exchanging timestampinformation, wherein each sensor has a clock. The method includes thesteps of receiving, at the plurality of sensors, a series of dataacquisition requests having a predefined time interval between the dataacquisition requests, wherein each data acquisition request includes anindex. The sensors record timestamps for each received request accordingto the clock of each sensor and determine a clock value to start dataacquisition for each timestamp at each sensor based on the timestamps,the respective index, and the predefined time interval. By selecting aminimum clock value for each sensor from the respective clock values,the sensors determine when to start data acquisition for the respectivesensor.

In one embodiment, a series of clock values t_(j) ^((k)) is processed todetermine the clock values t_(aj) ^((k)) using a formula t_(aj)^((k))=t_(j) ^((k))+(M−j)Δ+δ, where t_(j) ^((k)) denotes the timestamps,“k” denotes a particular sensor, “j” denotes a number of messages sentin the series, “δ” denotes a time delay, “Δ” denotes the predefined timeinterval, and “M” denotes a number of messages in the series.

In another embodiment, a series of clock values t_(j) ^((k)) isprocessed to determine the clock values t_(aj) ^((k)) using a formulat_(aj) ^((k))=t_(j) ^((k))+iΔ+δ, where t_(j) ^((k)) denotes thetimestamps, “k” denotes a particular sensor, “i” denotes a number ofmessages left in the series as the index, “δ” denotes a time delay, and“Δ” denotes the predefined time interval.

The method may also include the step of using a base station to send atleast one data acquisition request. An optional synchronization node mayreceive the at least one data acquisition request and, in turn, send theseries of data acquisition requests. For robustness, the sensors canbegin collecting data at the minimum clock value calculated even if thecomplete series has not been received.

In another embodiment, the subject technology is a method including thesteps of receiving, at the plurality of sensors, a series of dataacquisition requests having a predefined time interval Δ between thedata acquisition requests, wherein each data acquisition requestincludes an index “j”, recording timestamps t_(j) ^((k)) for eachreceived request according to the clock of each sensor, wherein “k”denotes an index of a particular sensor, and calculating a clock valuet_(a) ^((k)) for starting data acquisition at each sensor based upon thepredefined time interval Δ, the index “j” and the recorded timestampst_(j) ^((k)). In one embodiment, data acquisition is not done for eachtimestamp but rather data acquisition occurs after all timestamps arerecorded and then processed.

The method may also determine a time to start the data acquisition byselecting a minimum calculated clock value t_(a) ^((k)) for each sensoras the time to start the data acquisition for each sensor. The minimumof the clock values t_(a) ^((k)) can be used to reset the sensors clocksto a predefined value.

The method can also calculate a mean value of the clock values t_(a)^((k)) and use the mean value to determine a time to start the dataacquisition for the respective sensor or calculate a median value of theestimated clock values t_(a) ^((k)) and use the median value todetermine a time to start the data acquisition for the respectivesensor. A base station can send at least one data acquisition request orthe series of data acquisition requests. If the base station sends onlyone data acquisition request, an optional synchronization node canreceive the at least one data acquisition request and, in turn, send theseries of data acquisition requests to the sensors.

One embodiment is a sensor network including a plurality of sensors anda base station for sending a series of data acquisition requests to thesensors. Each data acquisition request has an index. Each sensor has asynchronization calculation module and an internal clock. The sensorsare adapted and configured to receive the series of data acquisitionrequests and record a timestamp of receipt for each data acquisitionrequest. The sensors also store a predefined time interval related tothe plurality of data acquisition requests so that the sensor cancalculate a time to start acquiring data based upon the series of dataacquisition requests, the timestamps, the indices, and the predefinedtime interval. In an alternative embodiment, the base station only sendsa general request for data acquisition and a synchronization sensormodule receives the general request and, in turn, sends the series ofdata acquisition requests to the sensors. The time can be equal to theindex times the predefined time interval plus the respective timestampand an offset. The offset can be zero or any sufficient amount of timeto provide robust synchronization. In one embodiment, the offset isequal to the predefined time interval. In one embodiment, once thesensors acquire data, transmission to the base station is controlledrelative to the time to avoid energy waste from sensor radio componentswaiting to transmit acquired data.

It should be appreciated that the present technology can be implementedand utilized in numerous ways, including without limitation as aprocess, an apparatus, a system, a device, a method for applications nowknown and later developed or a computer readable medium. These and otherunique features of the system disclosed herein will become more readilyapparent from the following description and the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

So that those having ordinary skill in the art to which the disclosedsystem appertains will more readily understand how to make and use thesame, reference may be had to the following drawings.

FIG. 1 is a schematic representation of a sensor system having wirelesssensors for utilizing synchronization methods in accordance with thesubject technology.

FIG. 2 is an exemplary series of messages between the base station andexemplary two wireless sensors in accordance with the subjecttechnology.

FIG. 3 is a schematic representation of the synchronization calculationsfor two sensors and four messages in accordance with the subjecttechnology.

FIG. 4 is a schematic representation of another sensor system havingwireless sensors utilizing a synchronization source node in accordancewith the subject technology.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The present disclosure overcomes many of the prior art problemsassociated with synchronizing wireless systems. The advantages, andother features of the system disclosed herein, will become more readilyapparent to those having ordinary skill in the art from the followingdetailed description of certain preferred embodiments taken inconjunction with the drawings which set forth representative embodimentsof the present invention and wherein like reference letters and numeralsidentify similar structural elements.

Now referring to FIG. 1, a schematic representation of a sensor system100 utilizing synchronization methods in accordance with the subjecttechnology is shown. The sensor system 100 includes a base station 102in wireless communication with a plurality of wireless devices such assensors or sensor nodes 104. The following description pertains tosensor applications but it is envisioned that the subject technology iswell-suited to any other wireless communication devices such as thosethat switch or create actions or simply controllers associated with thesame. Typically, the base station 102 serves as a data concentrator andthe wireless sensors 104 need to perform data acquisitionsimultaneously. The base station 102 may also be connected to aplurality of other sensors, whether wired or not, that do not requiresynchronization. In the sensor system 100, there are N sensors 104,wherein N may be any number and the sensors 104 are individuallyidentified as S1-SN for ease of reference. Each sensor 104 includes asynchronization calculation module 106.

To acquire data synchronously from the sensors, the base station 102sends a series of data acquisition requests or messages to all thesensors 104 using a broadcast or multicast mode, wherein a multicast iswhen the broadcast is to selected devices. There are a predeterminednumber of at least two data acquisition requests sent to all the sensors104. The interval between the consecutive requests is known to both thebase station 102 and the sensors 104. Preferably, the base station 102includes a precise clock to schedule the series of data acquisitionrequests in the designated intervals to create the predetermined gapsbetween messages.

Notably, the data acquisition requests do not include timestampinformation, which reduces the size of the data packet and associatedtransmission time. Instead, each data acquisition request includes asequence number from 1 to M, wherein M represents any number ofmessages. By including a sequence number, the wireless sensors 104 areprovided with the necessary information to determine the consecutivenumber of messages received. The numbering of the messages may be from 1to M or in reverse from M to 1.

However, the sensors 104 do not respond to the acquisition requestsimmediately. Instead, each sensor 104 receives the messages, records thearrival times, and performs synchronization calculations in thesynchronization calculation module 106 to establish the time to beginthe respective data acquisition. Each sensor 104 performs thesecalculations independently without further communication with the basestation 102 or between the sensors 104.

Once the sensors 104 complete the calculations, the sensors 104 areready to perform the data acquisitions. Preferably, the sensors 104 alsoinclude precise clocks (not shown) to schedule the calculated actions.Although the sensor clocks do not need to be synchronized, the clockrates being the same or similar facilitates accuracy in thesynchronization process. Similarly, the base station 102 has alsodetermined when the sensors 104 are to acquire data.

Once the data acquisition period has passed, the base station 102 sendsindividual data requests to all of the sensors 104. Each sensor 104responds to the data request with the respective set of acquired data.For large data sets, the data may be divided into packets and sent inconsecutive messages.

Referring now to FIG. 2, an exemplary series of messages between thebase station 102 and an exemplary two wireless sensors 104 in accordancewith the subject technology is shown. Although only S1 and S2 wirelesssensors 104 are shown, the subject technology is applicable to anynumber of sensors 104.

Acquisition Request Sequence

FIG. 2 illustrates the acquisition request sequence. Initially, M dataacquisition requests or messages (denoted by M and a sequential number)are sent by the base station 102 at time instances spaced precisely withtime interval Δ. As wireless transmissions may not arrive at the sensors104 with the spacing of Δ due to the inherent uncertain nature ofwireless communication, the receipt at the sensors 104 is effectivelyrandomly delayed. The respective times of receipt at the sensors 104 aredenoted by t_(j) ⁽¹⁾ and t_(j) ⁽²⁾, respectively. FIG. 2 also depictsthe interval between message for S1 sensor 104 as Δ_(kj) ⁽¹⁾ and for S2sensor 104 as Δ_(kj) ⁽²⁾.

For example, the time interval Δ₃₂ ⁽²⁾t₃ ⁽²⁾−t₂ ⁽²⁾ is shorter than Δbecause the second message M2 is delivered at S2 sensor 104 later thanat S1 sensor 104 (e.g., relatively delayed) while the third message M3is delivered relatively earlier. Similarly, the time interval Δ₃₂ ⁽¹⁾=t₃⁽¹⁾−t₂ ⁽¹⁾ is longer than Δ because the second message M2 is relativelypromptly delivered at S1 sensor 104 while the third message M3 isrelatively delayed in delivery at S1 sensor 104. With random errorintroduction, it is not possible to accurately predict the timing of thedelivery of the messages M.

Synchronization Calculations

As can be seen from FIG. 2, each sensor 104 records the time at whichthe acquisition request messages are received but does not have anyinformation regarding when other sensors received the same message.Although the delivery delays are random, it can be assumed that somemessages are delivered with minimal or small delays. For these promptlydelivered messages, the time for the message to propagate isdeterministic. In other words, the random component of the delay isminimized. If the sensors 104 can determine which messages are deliveredwith the smallest random delay component, then that message is desirablyused as the synchronization basis. In the sensor system 100, the sensors104 determine which of the messages represents the smallest time delaybased upon the receipt timestamps t_(j) ^((k)) as described herein withrespect to FIG. 3.

Referring now to FIG. 3, the synchronization calculations are shownschematically for two sensors 104 (e.g., N=2) and four messages (M=4).Generally, when the sensors 104 receive the j-th data acquisitionrequest from the base station 102, the sensors 104 note the receipttimestamp t_(j) ^((k)). The data acquisition request does include aserial number j as part of the message. As the sensor expects Macquisition requests to be sent from the base station, the number ofmessages yet to arrive is M−j. Thus, the time for delivery of the lastmessage is estimated to be (M−j)Δ.

Without random delays, the data acquisition could be scheduled to startat time t_(j) ^((k))+(M−j)Δ. However, due to the random delays, someadditional time margin δ may be required to start the data processingand acquisition. Thus, the time calculated by the synchronizationcalculation modules 106 to schedule the acquisition is t_(aj)^((k))=t_(j) ^((k))+(M−j)Δ+δ. Upon completion of receipt of M dataacquisition requests, each sensor has calculated M estimates of t_(aj)^((k)). The sensors 104 select the minimum of the estimates as the timeto start the data acquisition, i.e., t_(a) ^((k))=min (t_(aj) ^((k)))assuming that this minimum likely corresponded to the minimal randomdelay, which corresponds to the best choice for scheduling purposes.

Referring more particularly to FIG. 3, for S1 sensor 104, the secondmessage M2 was received the fastest. Thus, the corresponding estimatefor the minimal value of the four t_(aj) ⁽¹⁾ times is t_(a2) ⁽¹⁾=t₂⁽¹⁾+(4−2)Δ+δ. For S2 sensor 104, the first message M1 was received thefastest. Thus, the corresponding estimate for the minimal value of thefour times t_(aj) ⁽²⁾ is t_(a1) ⁽²⁾=t₁ ⁽²⁾+(4−1)Δ+δ. As can be seen, twoestimates t_(a) ⁽¹⁾=t_(a2) ⁽¹⁾ and t_(a) ⁽²⁾=t_(a1) ⁽²⁾ correspond totime instants that are very close to each other even though for eachradio message, the receipt timestamps on both sensors 104 weredifferent.

Preferably, the time margin δ is large enough so that none of theestimates t_(aJ) ^((k))=t_(j) ^((k))+(M−j)Δ+δ is less than the lastreceipt timestamp t_(M) ^((k)) corresponding to the M-th message. Insome configurations, the random variability of the message delay may bedistributed approximately according to a uniform distribution. Then, thetime margin δ is chosen as greater than the width of the delaydistribution.

In configurations where the random delays are not bounded, the sensors104 may stop waiting for additional messages when the clock reaches theminimal of the estimates calculated at that time. For example, afterreceipt of each message, the sensors 104 update the best or minimalestimate calculated from the messages received. When the clock valuereaches that minimal estimate, the sensors 104 start the dataacquisition without waiting for any new messages. It is envisioned thatthe actual data acquisition may be triggered at a desired time through,for example, a timer-based interrupt.

In one embodiment, the value of the time interval Δ may be adjusted bythe base station 102 during sensor system 100 operation according to theoperating environment. The new value of the time interval Δ is simplycommunicated to the sensors 104 in a separate message prior to thesynchronization process or even included with the data acquisitionrequests.

The choice of the time margin δ depends upon the implementation of thesoftware in the sensor system 100. In one embodiment, the value for thetime margin δ is zero. For example, the sensor system 100 may employinterrupt-driven data acquisition. When the clock reaches the minimalvalue t_(a) ^((k)), then any message arriving after that time instantwill not lead to any changes in scheduling. As a result, any subsequentmessages may be ignored and the sensor 104 proceeds to data acquisitiondirectly. In another embodiment, the sensor system 100 processes anymessages already in the queue prior to starting data acquisition. Inthis embodiment, it is preferable to utilize a time margin δ that islarge enough to guarantee that all messages are processed prior to t_(a)^((k)). Additionally, the time margin δ may be set equal to the timeinterval Δ to simplify calculations.

Dealing with Message Losses

If some of the messages are lost, then synchronization accuracy may beaffected. Consequently, the number M of messages sent should be largeenough so that the number of messages received creates a robust systemwith the desired accuracy level. As noted above, by starting dataacquisition when the minimum calculated start time occurs, the sensors104 will not be hung up awaiting delivery of all the messages. Ifadditional preparatory actions are required prior to starting dataacquisition, a preparatory time delay d may be chosen so that thewaiting for the last message is broken when the clock reaches t_(a)^((k))−d. Preferably, the preparatory time delay d is less than the timemargin δ.

Reverse Message Counting

In view of the possibility of some messages being lost, it is desirableto have each data acquisition request include the number of remainingmessages to be sent (e.g., M−j) instead of the number of messages sent(e.g., j) for use in the calculation of the time to start the dataacquisition t_(aJ) ^((k))=t_(j) ^((k))+(M−j)Δ+δ. In effect, the sensorsystem 100 uses reverse message counting from M−1 to zero instead ofcounting up from 1 to M. Advantageously, the sensors 104 do not need toknow the total number of messages to be sent by the base station 102. Ifa sent index i is used to represent the number of messages remaining,then the scheduled start time formula becomes t_(aJ) ^((k))=t_(j)^((k))+iΔ+δ. In another embodiment, the reverse message counting goesfrom M to 1, in which case the scheduled start time formula becomest_(aj) ^((k))=t_(j) ^((k))+(i−1)Δ+δ. As long as the message index idecreases by 1, a variety of schemes can be used.

Statistical Approaches to Calculating the Data Acquisition Time

Using the minimum formula of t_(a) ^((k))=min t_(aj) ^((k)) forcalculating the data acquisition time is a generally applicableapproach. However, if the statistical distribution of random messagedelivery delays is known, an alternative method of computing the dataacquisition time t_(a) ^((k)) based on the collection of individualvalues t_(aj) ^((k)) may be used. Estimation theory can derive the bestestimate for the particular statistical distribution and for theparticular quality criterion. For example, see Chapter 4 of “TheBayesian Choice” by Christian P. Robert (published by SpringerScience+Business Media, LLC in the year 2007) which addresses theoptimal parameter estimation problem. Preferably, the sensor system 100uses the same approach for each sensor 104.

Scheduling Sensor Clocks

An alternative method to scheduling the sensor data acquisition time isto adjust or synchronize the sensor clocks. Instead of starting the dataacquisition at time t_(a) ^((k)), the sensor clocks are reset to zero oranother predefined value. Thus at time t_(a) ^((k)), the sensors 104have clocks that are tightly synchronized. The synchronized sensors 104can then schedule actions that should take place simultaneously andcorrelate data between multiple sensors 104.

Switching Off Sensor Radios

As can be seen from the subject disclosure, the data traffic is reducedand the sensors do not need to transmit data during the synchronizationprocess. Consequently, the radio usage and associated power consumptionis reduced. Further, once the sensors 104 have received and processedthe last data acquisition request message, a radio component of thesensor 104 may be simply turned off or put into a low-power sleep modefor the duration of the data acquisition. The radio component may evenbe turned off before the data acquisition period such as at the timet_(a) ^((k))−d.

Upon completion of the data acquisition, the sensors 104 switch theradio components on and off as necessary to transmit the acquired data.It is also envisioned that instead of switching components on and off,the component may simply be put in a low power sleep mode to allow forfast wake up. The timing of the data transmission is also tightlycontrolled relative to the calculated start data acquisition time t_(a)^((k)). Thus, further energy waste is avoided by not having the sensorradio components on while waiting to transmit acquired data.

Synchronization Source Node Embodiment

Now referring to FIG. 4, another embodiment of a sensor system 200 inaccordance with the subject technology is shown. As will be appreciatedby those of ordinary skill in the pertinent art, the sensor system 200utilizes similar principles to the sensor system 100 described above.Accordingly, like reference numerals preceded by the numeral “2” insteadof the numeral “1”, are used to indicate like elements. The primarydifference of the sensor system 200 in comparison to the sensor system100 is the addition of a synchronization source node 208. Thesynchronization source node 208 allows removing the base station 202from the synchronization process. For example, the base station 202 maybe from a different vendor and use different standards for communicationand the like than the sensors 204 or simply not support the specificsynchronization process. The synchronization source node 208 may be asensor configured such that the synchronization source node 208 does notneed to be tightly synchronized with the other sensors 204. In anotherembodiment, the synchronization source node 208 is simply additionalhardware to facilitate the synchronization process.

During synchronization of the sensor system 200, the base station 202sends the same data acquisition request broadcast to all sensors 204without any additional synchronization information. However, the sensors204 ignore this base station request. Upon receiving the base stationrequest, the synchronization source node 208 begins sending a series ofM data acquisition request broadcasts (or multicasts) directed to allthe sensors 204. Then, the sensors 204 perform the synchronizationprocess as described above. After acquisition of the data, the sensors204 communicate directly with the base station 202 so that, from theperspective of the base station 202, the data acquisition and reportingprocess is unchanged. But, the synchronization source node 208 hastranslated the single request by the base station 202 into the requiredseries of request messages that enable the synchronization process.

It is envisioned that the subject technology includes adjusting thenumber of messages sent to advantageously perform synchronization whileminimizing the time and energy used for the synchronization process. Oneor more of the messages in the series may also include the total numberof messages in the series. Further, the subject technology is notlimited to sensor applications and may synchronize any type of devicesnow known or later developed.

While the invention has been described with respect to preferredembodiments, those skilled in the art will readily appreciate thatvarious changes and/or modifications can be made to the inventionwithout departing from the spirit or scope of the invention as definedby the appended claims. For example, each claim may depend from any orall claims in a multiple dependent manner even though such has not beenoriginally claimed.

What is claimed is:
 1. A method for synchronizing a plurality ofwireless devices without exchanging timestamp information, wherein eachwireless device has a clock, the method comprising the steps of:receiving, at the plurality of wireless devices, a series of dataacquisition requests having a predefined time interval between the dataacquisition requests, wherein each data acquisition request includes anindex; recording timestamps for each received request according to theclock of each wireless device; determining a clock value to start dataacquisition for each timestamp at each wireless device based on thetimestamps, the respective index, and the predefined time interval; andselecting a minimum clock value for each wireless device from therespective clock values as an instant to start data acquisition for therespective wireless device.
 2. A method as recited in claim 1, wherein aseries of clock values t_(j) ^((k)) is processed to determine the clockvalues t_(aj) ^((k)) using a formula t_(aj) ^((k))=t_(j)^((k))+(M−j)Δ+δ, where t_(j) ^((k)) denotes the timestamps, “k” denotesa particular wireless device, “j” denotes a number of messages sent inthe series, “δ” denotes a time delay, “Δ” denotes the predefined timeinterval, and “M” denotes a number of messages in the series.
 3. Amethod as recited in claim 1, wherein a series of clock values t_(j)^((k)) is processed to determine the clock values t_(aj) ^((k)) using aformula t_(aj) ^((k))=t_(j) ^((k))+iΔ+δ, where t_(j) ^((k)) denotes thetimestamps, “k” denotes a particular wireless device, “i” denotes anumber of messages left in the series as the index, “δ” denotes a timedelay, and “Δ” denotes the predefined time interval.
 4. A method asrecited in claim 1, further comprising the step of using a base stationto send at least one data acquisition request.
 5. A method as recited inclaim 4, further comprising the step of using a synchronization node toreceive the at least one data acquisition request and, in turn, send theseries of data acquisition requests.
 6. A method as recited in claim 1,wherein the wireless devices are sensors and the sensors begincollecting data at the minimum clock value calculated even if thecomplete series has not been received.
 7. A method for synchronizing aplurality of sensors without timestamp information, wherein each sensorhas a clock, the method comprising the steps of: receiving, at theplurality of sensors, a series of data acquisition requests having apredefined time interval Δ between the data acquisition requests,wherein each data acquisition request includes an index “j”; recordingtimestamps t_(j) ^((k)) for each received request according to the clockof each sensor, wherein “k” denotes the number of sensors; andcalculating a clock value t_(a) ^((k)) for starting data acquisition ateach sensor for each timestamp t_(j) ^((k)) based upon the predefinedtime interval Δ, the index “j” and the timestamps (k).
 8. A method asrecited in claim 7, further comprising the step of determining a time tostart the data acquisition by selecting a smallest calculated clockvalue t_(a) ^((k)) for each sensor as the time to start the dataacquisition for each sensor.
 9. A method as recited in claim 7, whereina smallest of the clock values t_(a) ^((k)) is used to reset the sensorsclocks to a predefined value.
 10. A method as recited in claim 7,further comprising the step of calculating a mean value of the clockvalues t_(a) ^((k)) and using the mean value to determine a time tostart the data acquisition for the respective sensor.
 11. A method asrecited in claim 7, further comprising the step of calculating a medianvalue of the estimated clock values t_(a) ^((k)) and using the medianvalue to determine a time to start the data acquisition for therespective sensor.
 12. A method as recited in claim 7, furthercomprising the step of using a base station to send at least one dataacquisition request.
 13. A method as recited in claim 12, wherein thebase station sends the series of data acquisition requests.
 14. A methodas recited in claim 12, further comprising the step of using asynchronization node to receive the at least one data acquisitionrequest and, in turn, send the series of data acquisition requests. 15.A sensor network comprising: a plurality of sensors, each sensor havingan internal clock, wherein the sensors are adapted and configured to:receive a series of data acquisition requests, wherein each dataacquisition request has an index; record a timestamp of receipt for eachdata acquisition request; store a predefined time interval related tothe plurality of data acquisition requests; and calculate a time tostart collecting data based upon the series of data acquisitionrequests, the timestamps, the indices, and the predefined time interval.16. A sensor network as recited in claim 15, wherein the time is equalto the index times the predefined time interval plus the respectivetimestamp and an offset.
 17. A sensor network as recited in claim 16,wherein the offset is approximately equal to the predefined timeinterval.
 18. A sensor network as recited in claim 15, furthercomprising a base station for sending the series.
 19. A sensor networkas recited in claim 18, wherein once the sensors acquire data,transmission to the base station is controlled relative to the time toavoid energy waste from sensor radio components waiting to transmitacquired data.
 20. A sensor network as recited in claim 15, furthercomprising a base station for sending a general request for dataacquisition and a synchronization sensor module for receiving thegeneral request and, in turn, sending the series.